This study investigates how backgrounded membrane imaging (BMI) can be used in combination with convolutional neural networks (CNNs) in order to quantitatively and qualitatively study subvisible particles in both protein biopharmaceuticals and samples containing synthetic model particles. BMI requires low sample volumes and avoids many technical complications associated with imaging particles in solution, e.g., air bubble interference, low refractive index contrast between solution and particles of interest, etc. Hence, BMI is an attractive technique for characterizing particles at various stages of drug product development. However, to date, the morphological information encoded in brightfield BMI images has scarcely been utilized. Here we show that CNN based methods can be useful in extracting morphological information from (label-free) brightfield BMI particle images. Images of particles from biopharmaceutical products and from laboratory prepared samples were analyzed with two types of CNN based approaches: traditional supervised classifiers and a recently proposed fingerprinting analysis method. We demonstrate that the CNN based methods are able to efficiently leverage BMI data to distinguish between particles comprised of different proteins, various fatty acids (representing polysorbate degradation related particles), and protein surrogates (NIST ETFE reference material) only based on BMI images. The utility of using the fingerprinting method for comparing morphological differences and similarities of particles formed in distinct drug products and/or laboratory prepared samples is further demonstrated and discussed through three case studies.

In order to study how polyphenols and vitamin C (vitC) together affect protein aggregation to amyloid fibrils, we performed similar in vitro studies as before using stefin B as a model and a potentially amyloid-forming protein (it aggregates upon overexpression, under stressful conditions and some progressive myoclonus epilepsy of tape 1-EPM1-missense mutations). In addition to the chosen polyphenol, this time, we added a proven antioxidant concentration of 0.5 mM vitC into the fibrillation mixture and varied concentrations of resveratrol, quercetin, and curcumin. Synergy with vitC was observed with curcumin and quercetin.

A mechanistic model for describing unfolding of a monoclonal antibody (mAb) in ion exchange chromatography has been developed. The model reproduced retention behavior characteristic for conformational changes of antibodies upon adsorption, including: multi-peak elution, aggregate formation, and recovery reduction. Two competitive paths in the adsorption mechanism of the unfolded protein were assumed: refolding in the adsorbed phase to the native form followed by its desorption, or direct desorption followed by instantaneous aggregation in the liquid phase. The reduction in recovery of the eluted protein was attributed to spreading of the unfolded protein on the adsorbent surface, which enhanced the binding affinity. The model was formulated based on the analysis of retention behavior of a model mAb that was eluted in pH gradients on a strong cation exchange resin. The pH profile was found to be distorted in the presence of the protein, which was ascribed to dissociation of ionizable groups of the protein in the adsorbed phase. Since the protein retention was strongly pH dependent, that phenomenon was also accounted for in mathematical modeling. A series of independent experiments was designed to evaluate the model parameters that quantified the process thermodynamics and kinetics: the Henry constants of the native, unfolded, spread and aggregated forms of the protein along with underlying kinetic coefficients. The model was efficient in reproducing the retention pattern of the protein and the aggregate content in eluting band profiles. After proper calibration, the model can potentially be used to quantify protein unfolding and elution in other ion exchange systems.

Biological systems are inherently complex, and the increasing level of detail with which we are able to experimentally probe such systems continually reveals new complexity. Fortunately, mathematical models are uniquely positioned to provide a tool suitable for rigorous analysis, hypothesis generation, and connecting results from isolated in vitro experiments with results from in vivo and whole-organism studies. However, developing useful mathematical models is challenging because of the often different domains of knowledge required in both math and biology. In this work, we endeavor to provide a useful guide for researchers interested in incorporating mathematical modeling into their scientific process. We advocate for the use of conceptual diagrams as a starting place to anchor researchers from both domains. These diagrams are useful for simplifying the biological process in question and distinguishing the essential components. Not only do they serve as the basis for developing a variety of mathematical models, but they ensure that any mathematical formulation of the biological system is led primarily by scientific questions. We provide a specific example of this process from our own work in studying prion aggregation to show the power of mathematical models to synergistically interact with experiments and push forward biological understanding. Choosing the most suitable model also depends on many different factors, and we consider how to make these choices based on different scales of biological organization and available data. We close by discussing the many opportunities that abound for both experimentalists and modelers to take advantage of collaborative work in this field.

The present work introduces new anti-aggregation agent (AAA) derived through our new approach for design and evaluation of anti-aggregation agent as a multi-purpose excipient to combat protein aggregation. Therapeutic proteins undergo aggregation due to even minor changes in environmental conditions like temperature, pH, shear and stress. Excipients play a vital role in prevention of aggregation. To stabilize a protein formulation different classes of excipients are used in combination after carefully selecting through laborious and time consuming trial and error experiments. To resolve these concerns, we have developed a rational approach based on molecular docking analysis and have designed, synthesized AAAs, and validated the approach by experimental studies. Trehalose phenylalaninate (TPA) has been synthesized and evaluated for stabilization of Bovine serum albumin (BSA). TPA was found to be non-toxic with a LC50 of >80μg/ml. BSA solutions with and without TPA were subjected to thermal and agitation stress and aggregation was monitored using sophisticated analytical techniques. The helical structure of BSA was completely retained in stressed samples at 0.1% concentration of TPA. SEC-HPLC clearly demonstrated the absence of aggregates in presence of TPA. Although aggregation was not seen in fluorescence spectra but quenching due to TPA was evident. Moreover, molecular dynamics study on BSA-TPA complex showed lower RMSD.

The International Conference on Harmonization Q8 (R2) includes a requirement that \"Critical formulation attributes and process parameters are generally identified through an assessment of the extent to which their variation can impact the quality of the drug product,\" that is, the need to assess the robustness of a formulation. In this article, a quality-by-design-based definition of a \"robust formulation\" for a biopharmaceutical product is proposed and illustrated with a case study. A multivariate formulation robustness study was performed for a selected formulation of a monoclonal antibody to demonstrate acceptable quality at the target composition as well as at the edges of the allowable composition ranges and fulfillment of the end-of-shelf-life stability requirements of 36 months at the intended storage temperature (2°C-8°C). Extrapolation of 24 months\' formulation robustness data to end of shelf life showed that the MAb formulation was robust within the claimed formulation composition ranges. Based on this case study, we propose that a formulation can be claimed as \"robust\" if all drug substance and drug product critical quality attributes remain within their respective end-of-shelf-life critical quality attribute-acceptance criteria throughout the entire claimed formulation composition range.

Asymmetrical flow field-flow fractionation (afFFF) was used to investigate the properties of a plant-produced anthrax toxin protective antigen, pp-PA83. The afFFF fractogram consisted of two main peaks with molar masses similar to the molecular mass of pp-PA83 monomer. afFFF carrier solutions strongly influenced the ratio and the intensity of the two main peaks. These differences indicate that conformation changes in the pp-PA83 molecule occurred during the afFFF analysis. Similar fractograms were obtained for different pp-PA83 formulations when the afFFF carrier solution and the protein formulation were the same (or very similar). The data show that in specific cases, afFFF could be used to study protein conformation and document the importance of studying the influence of the carrier solution on afFFF.

The majority of in vitro investigations concerning protein aggregation have been performed in dilute systems, which poorly reflect the crowded in vivo scenario. Cell interior is highly crowded with soluble and insoluble macromolecules that alter macromolecular properties. Macromolecular crowding is known to enhance the rate and/or extent of protein aggregation. However, most of the understandings were derived from studies with α-rich or predominantly α-proteins. Indeed, α-proteins fold faster than β-proteins and conversion of α-helices to cross β-sheets are responsible for aggregate/amyloid formation. Therefore, it is important to investigate how macromolecular crowding affects the aggregation propensity of β-rich proteins. In this study, we investigated the effect of synthetic macromolecular crowders on bovine carbonic anhydrase (BCA, a β-rich protein) aggregation. In contrast to the effect of macromolecular crowding on α-rich proteins, BCA aggregation was observed to be reduced due to decrease in the population of aggregation-prone intermediates as a consequence of increased native state stability. In addition, the extent of aggregation was found to depend on the nature of the crowder under consideration. Combining the published data on α-proteins and this study, we conclude that macromolecular crowding can have opposite consequences on protein aggregation process depending on the fold type of the protein.

Transient transfection of the human HEK293-EBNA1 cell line using polyethyleneimine is widely adopted for recombinant protein production. Whereas high expression of many targets is achieved, purification yields of some highly expressed proteins remain low due to aggregation. We hypothesized that for these proteins the expression rates achieved at standard transfection conditions are too high, causing an overload of the protein folding machinery. Here we present plasmid titration as an efficient method to vary expression rates for the optimization of soluble protein expression. In plasmid titration a dilution series of expression vector mixed with dummy plasmid is transfected in small scale cultures. Application to GFP shows that plasmid titration achieves a wide range of expression levels while maintaining high transfection efficiencies even at 500-fold plasmid dilution. Application of plasmid titration to selected Nod-like receptors (NLRs), which at standard conditions are highly expressed but poorly soluble, delays the onset of NLR aggregation and improves cell viability and the buildup of biomass. The amount of soluble protein depends on the combination of dilution factor and harvest day in a protein specific manner. For NOD1 50-fold plasmid dilution increases the amount of soluble protein approximately 5-fold. Due to its association with chaperones at all dilution factors tested we were unable to purify NOD1 to homogeneity. For NLRC4, which did not associate with chaperones, 10-fold plasmid dilution increased the purification yield 2-fold. This improvement, obtained with minimal effort due to the simplicity of the method, shows that reducing total expression may increase soluble protein yield.

Enormous strides have been made in the last 100 years to extend human life expectancy and to combat the major infectious diseases. Today, the major challenges for medical science are age-related diseases, including cancer, heart disease, lung disease, renal disease, and late-onset neurodegenerative disease. Of these, only the neurodegenerative diseases represent a class of disease so poorly understood that no general strategies for prevention or treatment exist. These diseases, which include Alzheimer\'s disease, Parkinson\'s disease, Huntington\'s disease, the transmissible spongiform encephalopathies, and amyotrophic lateral sclerosis (ALS), are generally fatal and incurable. The first section of this review summarizes the diversity and common features of the late-onset neurodegenerative diseases, with a particular focus on protein misfolding and aggregation-a recurring theme in the molecular pathology. The second section focuses on the particular case of ALS, a late-onset neurodegenerative disease characterized by the death of central nervous system motor neurons, leading to paralysis and patient death. Of the 10% of ALS cases that show familial inheritance (familial ALS), the largest subset is caused by mutations in the SOD1 gene, encoding the Cu, Zn superoxide dismutase (SOD1). The unusual kinetic stability of SOD1 has provided a unique opportunity for detailed structural characterization of conformational states potentially involved in SOD1-associated ALS. This review discusses past studies exploring the stability, folding, and misfolding behavior of SOD1, as well as the therapeutic possibilities of using detailed knowledge of misfolding pathways to target the molecular mechanisms underlying ALS and other neurodegenerative diseases.